?? houghpeaks.m
字號:
function [r, c, hnew] = houghpeaks(h, numpeaks, threshold, nhood)
%HOUGHPEAKS Detect peaks in Hough transform.
% [R, C, HNEW] = HOUGHPEAKS(H, NUMPEAKS, THRESHOLD, NHOOD) detects
% peaks in the Hough transform matrix H. NUMPEAKS specifies the
% maximum number of peak locations to look for. Values of H below
% THRESHOLD will not be considered to be peaks. NHOOD is a
% two-element vector specifying the size of the suppression
% neighborhood. This is the neighborhood around each peak that is
% set to zero after the peak is identified. The elements of NHOOD
% must be positive, odd integers. R and C are the row and column
% coordinates of the identified peaks. HNEW is the Hough transform
% with peak neighborhood suppressed.
%
% If NHOOD is omitted, it defaults to the smallest odd values >=
% size(H)/50. If THRESHOLD is omitted, it defaults to
% 0.5*max(H(:)). If NUMPEAKS is omitted, it defaults to 1.
% Copyright 2002-2004 R. C. Gonzalez, R. E. Woods, & S. L. Eddins
% Digital Image Processing Using MATLAB, Prentice-Hall, 2004
% $Revision: 1.5 $ $Date: 2003/11/21 13:34:50 $
if nargin < 4
nhood = size(h)/50;
% Make sure the neighborhood size is odd.
nhood = max(2*ceil(nhood/2) + 1, 1);
end
if nargin < 3
threshold = 0.5 * max(h(:));
end
if nargin < 2
numpeaks = 1;
end
done = false;
hnew = h; r = []; c = [];
while ~done
[p, q] = find(hnew == max(hnew(:)));
p = p(1); q = q(1);
if hnew(p, q) >= threshold
r(end + 1) = p; c(end + 1) = q;
% Suppress this maximum and its close neighbors.
p1 = p - (nhood(1) - 1)/2; p2 = p + (nhood(1) - 1)/2;
q1 = q - (nhood(2) - 1)/2; q2 = q + (nhood(2) - 1)/2;
[pp, qq] = ndgrid(p1:p2,q1:q2);
pp = pp(:); qq = qq(:);
% Throw away neighbor coordinates that are out of bounds in
% the rho direction.
badrho = find((pp < 1) | (pp > size(h, 1)));
pp(badrho) = []; qq(badrho) = [];
% For coordinates that are out of bounds in the theta
% direction, we want to consider that H is antisymmetric
% along the rho axis for theta = +/- 90 degrees.
theta_too_low = find(qq < 1);
qq(theta_too_low) = size(h, 2) + qq(theta_too_low);
pp(theta_too_low) = size(h, 1) - pp(theta_too_low) + 1;
theta_too_high = find(qq > size(h, 2));
qq(theta_too_high) = qq(theta_too_high) - size(h, 2);
pp(theta_too_high) = size(h, 1) - pp(theta_too_high) + 1;
% Convert to linear indices to zero out all the values.
hnew(sub2ind(size(hnew), pp, qq)) = 0;
done = length(r) == numpeaks;
else
done = true;
end
end
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